Operations | Monitoring | ITSM | DevOps | Cloud

Most internal AI projects for IT operations next exit pilot. Budgets stretch, priorities shift, key hires fall through, and what started as a strategic initiative turns into a maintenance burden—or worse, shelfware. Not because the teams lacked vision. But because building a production-grade AI agent is an open-ended commitment. It’s not just model tuning or pipeline orchestration. It’s everything: architecture, integrations, testing frameworks, feedback loops, governance, compliance.

About 15 years ago, I worked at a company building network security appliances (with ARM-based network processors) and was responsible for the development of custom Linux firmware. The product launch was successful; we shipped and managed a large fleet of devices in the field. After a few firmware releases, we received alerts from the device management system telling us that there were intermittent problems. Remoted into the appliances but could not reproduce the error.

Today’s digital businesses are more interconnected than ever. Industry research shows that 74% of organizations now take an “API-first” approach, and the average application is powered by between 26 and 50 APIs. While this accelerates innovation, it also introduces new risks: when an external provider fails, the impact can be immediate and far-reaching.

Last night, over dinner in Canary Wharf, I found myself catching up with a former colleague who is now leading investments at one of the big banks.

When looking at the broad landscape of IT automation tools, you’ll find dozens (if not hundreds) of tools that seem like viable solutions to your automation needs. Almost all of those tools can be broken down into two categories: Open source automation tools and commercial automation tools. (Open source automation tools with a commercial offering are still considered open source, even if the commercial edition has a price tag.)

Node.js powers some of the fastest-growing web applications, but its single-threaded nature makes it vulnerable to memory leaks and CPU spikes. To keep your app running smoothly, especially in production, you need more than just web server logs — you need complete visibility across the entire stack.

Choosing the right APM tool is critical. How do you know which is the right one for you? Here are the top 13 open-source application performance monitoring(APM) tools that can solve your monitoring needs. Open-source APM tools have added benefits over their SaaS counterparts. They are more transparent, as you can verify their source code, and you can use them without going through the pains of obtaining approvals usually required for using a third-party vendor tool.